A spectrum analyzer is a measurement device used to examine the spectral composition of waveforms, such as electrical, acoustic, or optical waveforms. Often spectrum analyzers are also configured to measure the power spectrum of the waveforms over a particular frequency range. There are two types of spectrum analyzers: analog spectrum analyzers and digital spectrum analyzers. Generally, an analog spectrum analyzer uses either a variable band-pass filter whose mid-frequency is automatically tuned (shifted, swept) through the range of frequencies of which the spectrum is to be measured or a superheterodyne receiver where the local oscillator is swept through a range of frequencies. Generally, a digital spectrum analyzer computes the discrete Fourier transform (DFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.
More and more, spectrum analyzers are relied upon to provide accurate measurements of comparatively complex signals. For example, modern digital communications signals undergo comparatively complicated modulation schemes. These types of complex signals can tax the limits of performance of spectrum analyzers.
The performance of spectrum analyzers can be degraded by sources of signal distortion that are inherent within the spectrum analyzers. Thus, the spectrum analyzer can distort the spectrum of the signal under test (SUT). Notably, three sources of signal distortion are inherent to spectrum analyzers: broadband noise, phase noise and third order intermodulation (TOI) distortion. The noise sources result from, for example, local oscillators, frequency references and other components of the spectrum analyzer. The noise sources are power sums resulting from independent and uncorrelated processes. Thus, phase and broadband noise are scalars that add to the noise of the SUT. By contrast, TOI products from the spectrum analyzer are vectors that add to the TOI products of the SUT by coherent vector addition, leading to distortion of the TOI products of the SUT.
Noise and TOI products can reduce measurement accuracy of a spectrum analyzer when the noise and TOI products of the spectrum analyzer cannot be isolated from signal measurements that are performed by the spectrum analyzer. These noise and TOI products can also limit measurement sensitivity of the spectrum analyzer. If the noise and TOI products of the spectrum analyzer are sufficiently high relative to the signals being measured, the signals can be masked by the noise and TOI products of the spectrum analyzer and go undetected by the spectrum analyzer. Unfortunately, decreasing the noise of the spectrum analyzer and reducing the TOI products to improve the measurement accuracy and measurement sensitivity can be costly or difficult to achieve.